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2.0 - 6.0 years

0 Lacs

haryana

On-site

As an Analytics and Modeling Analyst at Accenture, you will be part of our growing Insights and Analytics team. You will be responsible for developing and implementing machine learning models using supervised and unsupervised techniques. Your role will involve applying appropriate machine learning algorithms for prediction tasks and data segmentation based on project requirements. Additionally, you will perform data preprocessing, feature engineering, and model evaluation to ensure the accuracy and efficiency of the models. The ideal candidate for this position should have a Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field, along with 2 to 3 years of experience in applied machine learning and data science projects. You should have a solid understanding of model training, validation, and deployment workflows, as well as experience working with version control and collaborative development environments. Familiarity with tools that automate and manage the process of building, testing, and deploying machine learning models, as well as a basic understanding of cloud-based architecture and APIs, would be beneficial. In this role, you will collaborate with data engineers, analysts, and product teams to translate business problems into machine learning solutions. You will use Python libraries such as scikit-learn, TensorFlow, and others to build and test models, and analyze and manipulate structured datasets using notebooks like Jupyter. Your responsibilities will also include documenting model performance, data flows, and process pipelines to ensure transparency and reproducibility of the work. If you are a Machine Learning Data Scientist with a passion for building ML models using cutting-edge techniques and technologies, we invite you to join our team at Accenture and contribute to creating value and shared success for our clients, people, and communities.,

Posted 2 days ago

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5.0 - 9.0 years

0 Lacs

karnataka

On-site

As a part of this role, you will be responsible for setting up a Center of Excellence (CoE) and business practice for Enterprise AI solutions. You will be tasked with establishing Data Science & Analytics as a Service (DaaS) and building a practice with capabilities to create solution blueprints and roadmaps, orchestrate data acquisition, management, and engineering, as well as develop AI/ML models to solve analytical problems. It will be essential to stay updated with industry trends and developments to ensure the practice remains cutting-edge. In addition, you will promote collaboration and engagement within the team and with stakeholders. Your responsibilities will include creating technical Proof of Concepts (POCs) and solution demos, driving discussions to evaluate and design AI/ML solutions for various engagements, and implementing a framework across the solutions development lifecycle phases. You will also be required to develop a value tracking mechanism to monitor the Return on Investment (ROI) for AI/ML projects. Furthermore, a key aspect of this role will involve hiring, training, and mentoring a team of AI/ML experts to deliver technical solutions based on AI/ML products and platforms. It will be crucial to possess technical skills such as expertise in AI/ML, statistical modeling, ML techniques, and concepts, as well as experience with agile software development methodology and big-data projects. You should also have a fair understanding of verticals like Insurance, Manufacturing, and Education. Moreover, familiarity with tools and techniques related to data preparation, movement, analysis, visualization, machine learning, and Natural Language Processing (NLP) is essential. Experience in AI/ML enabled solution development leveraging high volume and high-velocity data across disparate systems and supporting large-scale Enterprise analytical solutions will be advantageous. Additionally, having a vision and the ability to set up solution practice groups will be beneficial. In terms of technical skills, it is required to have experience with Spark/Spark MLlib, visualization tools like Tableau/Power BI/Qlik View, cloud platforms such as Azure ML/AWS SageMaker/Snowflake, ML Ops, Automated ML, NLP, and Image/Video Analytics. Non-technical skills like possessing a master's degree in relevant fields, excellent interpersonal and people skills, analytical mindset, good debugging skills, and strong verbal and written English communication skills are also mandatory. Overall, this role offers a challenging opportunity to lead and drive AI/ML initiatives within the organization, requiring a combination of technical expertise, leadership skills, and a passion for innovation in the field of data science and analytics.,

Posted 1 week ago

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